Social Traffic Sources Fixed with Google Analytics Filters

See how to implement filters and channel grouping settings to clean up messy social traffic sources.

Have you seen reports from Google Analytics with messy social sources that look something like this:

Source URLs from Pinterest:

Source URLs from Instagram:

Source URLs from Facebook:

Or even traffic from Facebook, Instagram, or Pinterest lumped into your (Other) Channel?

You’re not alone!

While not the end of the world, it can cause some annoyance for your dashboards if you’re pivoting off of Source / Medium, Source, or don’t have your have your Channel Groupings setup to capture these variations.

This how-to guide includes a few quick updates in Google Analytics to fix your social traffic source attribution by:

Implementing search & replace filters in GA to combine these into single source rows

Click Verify Filter one more time and you should see the same type of confirmation as the examples above.

Common Questions

You might be thinking that keeping sources like m.facebook vs facebook can help differentiate from mobile vs desktop visits – which is valid – however if you want to break this down then you can do so via secondary dimensions:

Also, it’s important to note that these filters are not retroactive. They will only clean data up going forward 🙁 .

Modify Social Channel Grouping Settings

If you prefer to live in the Acquisition > Channel Grouping reports then you might need to tweak your Channel Grouping settings to give you the attribution breakdown you’re expecting.

Bonus: If you prefer to break out Paid Social from Social (non-paid) then you can define another Channel called Paid Social with the rules below which will catch your paid links first (if you use “paid” in the campaign medium URL):

In this example, if visits have Source = facebook and Medium = social then they will not match this channel and will fall into your “Social” channel.

Conclusion

Unfortunately we can’t control referral hostname URLs from the plethora of social sites driving traffic to our sites. But we can unify these via the powerful filtering capabilities of Google Analytics.

The example filters above can be applied to any other traffic sources where you encounter this problem.

Be sure to always test these on test view in Google Analytics first so you don’t corrupt your production data!

If you’re interested in other ways to clean up channel and campaign reporting, read this guide on how to use GTM lookup table variables to automate campaign tagging for you.

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Brad Redding

Brad, co-founder of Elevar, has lived in eCommerce for over 12 years. He's helped design, build, and optimize over 100 websites in his career. From new retail startups to well-known brands like Le Creuset, Signature Hardware, Rebecca Minkoff, Char-Broil and more, he specializes in data analytics and conversion optimization to help achieve business goals.